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Language Signal Audit
x402
Language Signal Audit is a paid API for AI agents from agentreadiness.halowerk.com, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-14).
Passively audits a public URL or domain for language signal quality criteria and returns verdict, evidence, limitations, and recommended action
Price / call$0.001
Success—
StatusUnknown
How this service works
Language signal audit fetches current public evidence from the supplied target and evaluates the documented criterion. It returns the observation, threshold, verdict, exact evidence source, limitations and a mode-specific action. The check is passive: no login attempt, payload injection, exploit, purchase, form submission or load test is performed.
Output
Returns an observation describing what was found on the target, the threshold being evaluated, a pass/fail verdict, the exact evidence source URL or element, any limitations of the passive check, and a mode-specific recommended action — all without performing any login, form submission, or active exploit.
Example use cases
Pre-launch agent readiness check
“Before we launch the new product site at newproduct.acme.com, run a language signal audit on it and tell me if it passes, what evidence you found, and what we should fix.”
Competitor language signal benchmarking
“Audit competitor.io for language signals — I want to know their verdict, what evidence was detected, and how their setup compares to ours at ourdomain.com.”
Ongoing site monitoring for language quality
“Check docs.myplatform.dev for language signal compliance and let me know the verdict, the exact evidence source, any limitations in the audit, and what action we should take next.”
Technical details
Endpoint
POSThttps://agentreadiness.halowerk.com/v1/language-signal-audit?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a passive, read-only audit of language signal quality on a public URL or domain as part of an agent-readiness or LLM-compatibility workflow. It is purpose-built for evaluating whether a site's language structure meets documented criteria interpretable by AI agents, and returns structured verdict + evidence rather than raw HTML. Prefer it over generic scraping tools when you need a scored, criterion-based verdict with an action recommendation rather than raw content extraction.
Side effects
- Target URL is unreachable or returns non-200 status, resulting in no evidence collected
- Domain normalization fails for malformed URLs
- Rate limiting or bot protection on the target blocks passive inspection
- Baseline mismatch if supplied baseline schema is incompatible
- Insufficient public evidence to render a verdict, returning inconclusive result
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| target | string | Public HTTP(S) URL or domain to inspect. A bare domain is normalized to HTTPS. |
| context | object | Optional non-secret correlation labels returned unchanged only in the request lifecycle. |
| baseline | — | Optional baseline returned by a previous snapshot call. |
| compare_url | string | Optional public comparison URL. Used by change and monitoring services. |
Tags
x402
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